Review of technological progress in carbon dioxide capture, storage, and utilization

S Davoodi, M Al-Shargabi, DA Wood… - Gas Science and …, 2023‏ - Elsevier
Emissions of substantial amounts of greenhouse gases (GHG) accumulating in the
atmosphere have caused climate alterations and increased global temperatures. Several …

Exploring hydrogen geologic storage in China for future energy: Opportunities and challenges

Z Du, Z Dai, Z Yang, C Zhan, W Chen, M Cao… - … and Sustainable Energy …, 2024‏ - Elsevier
Hydrogen, as a clean and efficient energy source, is important in achieving zero-CO 2
targets. This paper explores the potential of hydrogen geologic storage (HGS) in China for …

Data-driven machine learning models for the prediction of hydrogen solubility in aqueous systems of varying salinity: Implications for underground hydrogen storage

HV Thanh, H Zhang, Z Dai, T Zhang… - International Journal of …, 2024‏ - Elsevier
Hydrogen is a clean and sustainable renewable energy source with significant potential for
use in energy storage applications because of its high energy density. In particular …

Improving predictions of shale wettability using advanced machine learning techniques and nature-inspired methods: Implications for carbon capture utilization and …

H Zhang, HV Thanh, M Rahimi, WJ Al-Mudhafar… - Science of The Total …, 2023‏ - Elsevier
The utilization of carbon capture utilization and storage (CCUS) in unconventional
formations is a promising way for improving hydrocarbon production and combating climate …

Machine-learning models to predict hydrogen uptake of porous carbon materials from influential variables

S Davoodi, HV Thanh, DA Wood, M Mehrad… - Separation and …, 2023‏ - Elsevier
Hydrogen (H 2) absorption percentage by porous carbon media (PCM) is important for
identifying efficient H 2 storage media. PCM with H 2-uptakes of greater than 5 wt% are …

Combined machine-learning and optimization models for predicting carbon dioxide trap** indexes in deep geological formations

S Davoodi, HV Thanh, DA Wood, M Mehrad… - Applied Soft …, 2023‏ - Elsevier
Emissions of carbon dioxide (CO 2) are a major source of atmospheric pollution contributing
to global warming. Carbon geological sequestration (CGS) in saline aquifers offers a …

Catalyzing net-zero carbon strategies: Enhancing CO2 flux Prediction from underground coal fires using optimized machine learning models

H Zhang, P Wang, M Rahimi, HV Thanh, Y Wang… - Journal of Cleaner …, 2024‏ - Elsevier
Underground coal fires release substantial carbon dioxide (CO 2), posing significant
environmental and health threats. Accurate prediction of surface CO 2 emissions in these …

Predicting uniaxial compressive strength from drilling variables aided by hybrid machine learning

S Davoodi, M Mehrad, DA Wood… - International Journal of …, 2023‏ - Elsevier
Awareness of uniaxial compressive strength (UCS) as a key rock formation parameter for the
design and development of gas and oil field plays. It plays an essential role in the selection …

Modeling the thermal transport properties of hydrogen and its mixtures with greenhouse gas impurities: A data-driven machine learning approach

HV Thanh, M Rahimi, S Tangparitkul… - International Journal of …, 2024‏ - Elsevier
This study introduces machine learning (ML) algorithms to predict hydrogen (H 2)
thermodynamic properties for geological storage, focusing on its mixtures with natural gas …

Machine learning insights to CO2-EOR and storage simulations through a five-spot pattern–a theoretical study

S Davoodi, HV Thanh, DA Wood, M Mehrad… - Expert Systems with …, 2024‏ - Elsevier
The utilization of CO 2 flooding is a widely applied enhanced oil recovery (EOR) technique
in mature onshore oil fields. As well as being able to increase oil production and recovery it …